Assessment of quantitative staging PET/computed tomography parameters using machine learning for early detection of progression in diffuse large B-cell lymphoma
Using quantitative parameters derived from staging PET with machine learning algorithms may enable us to detect early progression in patients with DLBCL and improve early risk stratification and guide treatment decisions in these patients.
Authors
- Anilcan Us
- Şerife Solmaz (ORCID: https://orcid.org/0000-0001-7180-3423)
- Kadir Alper Küçüker (ORCID: https://orcid.org/0000-0003-2535-7498)
- Bülent Turgut (ORCID: https://orcid.org/0000-0001-7443-1100)
- Ayşegül Aksu (ORCID: https://orcid.org/0000-0002-6239-0660)
Institutions
- Izmir Kâtip Çelebi University (TR)
Publication Details
- Journal
- Nuclear Medicine Communications
- Published
- 2025-06-30
- DOI
- https://doi.org/10.1097/mnm.0000000000002023
- Citations
- 1
- Primary Topic
- Lymphoma Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.47